predict

predict.py

from snap import *
import collections

FILENAME = 'FSlearn.csv'

def getNeighbors(G, i):
    neighborsV = TIntV()
    GetNodesAtHop(G, i, 1, neighborsV, False)
    return [i for i in neighborsV]

def maxPlace(places):
	maxi = 0
	maxj = 0
	for i,j in places:
		if i > maxi:
			maxi = i
			maxj = j

FInf = TFIn(FILENAME + 'predictions.bin')
Gf = TNEANet.Load(FInf)

nodes     = [i.GetId() for i in G.Nodes()]
people    = [i for i in nodes if i>0]
locations = [i for i in nodes if i<-1]


human = collections.defaultdict(lambda: [])

for i in locations:
	herd = Gf.GetIntAttrDatN(j, "herd")
	tail = Gf.GetIntAttrDatN(j, "tail")
	for j in people:

		friend = 0
		if G.IsEdge(i,j):
			friend += (Gf.GetIntAttrDatE( Gf.GetEId(i, j), "checkin" ) #todo checkin v friend

		human[j].append( (i, herd+tail+friend) )